Tabu Search with Delta Test for Time Series Prediction using OP-KNN
Antti Sorjamaa, Yoan Miché · 2008
Abstract. This paper presents a working combination of input selection strategy and a fast approximator for time series prediction. The input selection is performed using Tabu Search with the Delta Test. The approximation methodology is called Optimally-Pruned k-Nearest Neighbors (OP-KNN), which has been recently developed for fast and accurate regression and classification tasks. In this paper we demonstrate the accuracy of the OP-KNN with the Tabu Search using the ESTSP 2008 Competition datasets.